NIEHS-Led Collaboration Receives Director’s Challenge Nod
Photo: Steve McCaw/NIEHS
An NIEHS-led research collaboration has received the NIH Director’s Challenge Innovation Award.
Led by Dr. Dondrae Coble, chief of the Comparative Medicine Branch, the grant will fund construction of multiple animal enclosures designed to help researchers observe the effects of 115 environmental chemicals on behavior. The enclosures help ensure that observations are minimally disruptive to the research animals, which include fruit flies and mice.
Additionally, the researchers will use the grant to collect, analyze, store and share data collected during the experimentation process.
The goal is to narrow down from 115 to 10 environmental chemicals that are most likely to cause potential neurodevelopmental disorders in fruit flies and mice. Ultimately the information could help identify environmental chemicals causing neurodevelopmental disorders in human children.
The effort brings together collaborators from the NIEHS Division of Intramural Research and Division of the National Toxicology Program, NIDDK and NIBIB.
“The proposed project led by Dr. Coble, a recent NIEHS recruit from Nationwide Children’s Hospital and the Ohio State University, is highly meritorious and is precisely the type of innovative, high risk/high reward research that the NIH Intramural Research Program was designed to support,” said NIEHS scientific director Dr. Darryl Zeldin.
The award comes on the heels of previous NIEHS research also using holistic systems physiology—a method of doing animal modeling that measures the effects of environmental factors of multiple systems simultaneously—initiated by DNTP scientific director Dr. Brian Berridge. The method reduces the number of research animals while increasing the amount of information collected.
Photo: Steve McCaw/NIEHS
Developing the 24-hour observation instrumentation for the animal enclosures taps an unlikely source: the machine vision capabilities pioneered by autonomous vehicle research. Machine vision is when artificial intelligence (AI) is applied to processing images and video in real time using deep neural networks, which are used to train AI to pick out features and learn as it goes.
“There are many ways we’re tracking ourselves all the time—with smart watches, apps and sensors in our clothing—and now we’re building that into animal models,” said Dr. Jesse Cushman, director of the Neurobehavioral Core Laboratory.
Just as a self-driving car can tell the difference between a person and a stop sign, the machine vision used in the enclosures will be trained to tell the difference between behaviors that transcend species, such as grooming, eating, sleeping and interacting with others, as well as distinguish between species-specific behaviors like wing expansion in fruit flies and foraging in mice.
By observing how environmental chemicals affect the behavior of fruit flies and mice, the researchers can extrapolate those effects to how they might impact human development.
“Broadly, cross-species extrapolation is a foundation of what we do in science,” Cushman said. “Regulators put a lot of weight on these in vivo studies, but they’re very expensive and time consuming—which we’re trying to address with this approach. It’s critical to have in vivo data in the whole organism to understand the full impact the compounds have.
“Our goal,” he said, “is to create a high throughput, scalable, automated method to do behavioral research that is better for the animals. We see this as foundational technology to build in holistic perspectives.”
The Director’s Challenge identifies and funds projects that foster trans-NIH collaboration. The program provides seed money from the NIH Office of Intramural Research for innovative and high-impact research that shows significant benefit to a variety of infrastructure and/or scientific endeavors.
The award amount for “Machine vision-enabled behavioral tracking for cross-species extrapolation” is $500,000, spread over 2 years.